scholarly journals Dependence of cloud properties derived from spectrally resolved visible satellite observations on surface temperature

2008 ◽  
Vol 8 (9) ◽  
pp. 2299-2312 ◽  
Author(s):  
T. Wagner ◽  
S. Beirle ◽  
T. Deutschmann ◽  
M. Grzegorski ◽  
U. Platt
Keyword(s):  
Surface Temperature ◽  
Climate Models ◽  
Cloud Fraction ◽  
Satellite Observations ◽  
Climate Feedback ◽  
Climate Modelling ◽  
Radiative Feedback ◽  
Cloud Properties ◽  
Cloud Radiative Feedback ◽  
Spectrally Resolved

Abstract. Cloud climate feedback constitutes the most important uncertainty in climate modelling, and currently even its sign is still unknown. In the recently published report of the intergovernmental panel on climate change (IPCC), 6 out of 20 climate models showed a positive and 14 a negative cloud radiative feedback in a doubled CO2 scenario. The radiative budget of clouds has also been investigated by experimental methods, especially by studying the relation of satellite observed broad band shortwave and longwave radiation to sea surface temperature. Here we present a new method for the investigation of the dependence of cloud properties on temperature changes, derived from spectrally resolved satellite observations in the visible spectral range. Our study differs from previous investigations in three important ways: first, we directly extract cloud properties (effective cloud fraction and effective cloud top height) and relate them to surface temperature. Second, we retrieve the cloud altitude from the atmospheric O2 absorption instead from thermal IR radiation. Third, our correlation analysis is performed using 7.5 years of global monthly anomalies (with respect to the average of the same month for all years). For most parts of the globe (except the tropics) we find a negative correlation of effective cloud fraction versus surface-near temperature. In contrast, for the effective cloud top height a positive correlation is found for almost the whole globe. Both findings might serve as an indicator for an overall positive cloud radiative feedback. Another peculiarity of our study is that the cloud-temperature relationships are determined for fixed locations (instead to spatial variations over selected areas) and are based on the "natural" variability over several years (instead the anomaly for a strong El-Nino event). From a detailed comparison to cloud properties from the International Satellite Cloud Climatology Project (ISCCP), in general good agreement is found. However, also systematic differences occurred indicating that our results provide independent and complementary information on cloud properties. Climate models should thus aim to reproduce our findings. Recommendations for the development of a "processor" to convert model results into the cloud sensitive quantities observed by the satellite are given.

scholarly journals Dependence of cloud fraction and cloud top height on surface temperature derived from spectrally resolved UV/vis satellite observations

2007 ◽  
Vol 7 (6) ◽  
pp. 17117-17146
Author(s):  
T. Wagner ◽  
S. Beirle ◽  
T. Deutschmann ◽  
M. Grzegorski ◽  
U. Platt
Keyword(s):  
Surface Temperature ◽  
Climate Models ◽  
Broad Band ◽  
Cloud Fraction ◽  
Satellite Observations ◽  
Climate Feedback ◽  
Climate Modelling ◽  
Intergovernmental Panel ◽  
Cloud Properties ◽  
Spectrally Resolved

Abstract. Cloud climate feedback constitutes the most important uncertainty in climate modelling, and currently even its sign is still unknown. In the recently published report of the intergovernmental panel on climate change (IPCC), from 20 climate models 6 showed a positive and 14 a negative cloud radiative feedback in a doubled CO2 scenario. The radiative budget of clouds has also been investigated by experimental methods, especially by studying the relation of satellite observed broad band shortwave and longwave radiation to sea surface temperature. Here we present a new method for the investigation of the dependence of cloud properties on temperature changes, derived from spectrally resolved UV/vis satellite observations. Our study differs from previous investigations in three important ways: first, we directly extract cloud properties (amount and altitude) and relate them to surface temperature. Second, we retrieve the cloud altitude from the atmospheric O2 absorption instead from thermal IR radiation. Third, our correlation analysis is performed using 7.5 years of global monthly anomalies (with respect to the average of the same month for all years). For most parts of the globe (except the tropics) we find a negative correlation of cloud fraction versus surface-near temperature. In contrast, for the cloud top height a positive correlation is found for almost the whole globe. Both findings might serve as an indicator for an overall positive cloud climate feedback. Another peculiarity of our study is that the cloud-temperature relationships are determined for fixed locations (instead to spatial variations over selected areas) and are based on the "natural" variability over several years (instead the anomaly for a strong El-Nino event). Thus our results might be especially representative for the extrapolation to long term climate changes. Climate models should aim to reproduce our findings: if substantial differences are found, this might indicate that important details are not yet well captured by these models. If good agreement is found, from the models reliable information on the magnitude and the detail mechanisms of cloud climate feedback could be gained.

A Climatology of Clouds in Marine Cold Air Outbreaks in Both Hemispheres

2016 ◽  
Vol 29 (18) ◽  
pp. 6677-6692 ◽  
Author(s):  
Jennifer K. Fletcher ◽  
Shannon Mason ◽  
Christian Jakob
Keyword(s):  
Climate Models ◽  
Cloud Fraction ◽  
Satellite Observations ◽  
Radiative Effect ◽  
Cold Air ◽  
Cloud Properties ◽  
Cold Air Outbreak ◽  
Cloud Radiative Effect ◽  
Cold Air Outbreaks

Abstract A climatology of clouds within marine cold air outbreaks, primarily using long-term satellite observations, is presented. Cloud properties between cold air outbreaks in different regions in both hemispheres are compared. In all regions marine cold air outbreak clouds tend to be low level with high cloud fraction and low-to-moderate optical thickness. Stronger cold air outbreaks have clouds that are optically thicker, but not geometrically thicker, than those in weaker cold air outbreaks. There is some evidence that clouds deepen and break up over the course of a cold air outbreak event. The top-of-the-atmosphere longwave cloud radiative effect in cold air outbreaks is small because the clouds have low tops. However, their surface longwave cloud radiative effect is considerably larger. The rarity of cold air outbreaks in summer limits their shortwave cloud radiative effect. They do not contribute substantially to global shortwave cloud radiative effect and are, therefore, unlikely to be a major source of shortwave cloud radiative effect errors in climate models.

scholarly journals Atmospheric circulation and hydroclimate impacts of alternative warming scenarios for the Eocene

2017 ◽  
Vol 13 (8) ◽  
pp. 1037-1048 ◽  
Author(s):  
Henrik Carlson ◽  
Rodrigo Caballero
Keyword(s):  
Surface Temperature ◽  
Radiative Forcing ◽  
Climate Models ◽  
Climate Model ◽  
Regional Climate ◽  
Warm Season ◽  
Cloud Albedo ◽  
Cloud Properties ◽  
Atmospheric Co2 Concentrations ◽  
Global Mean

Abstract. Recent work in modelling the warm climates of the early Eocene shows that it is possible to obtain a reasonable global match between model surface temperature and proxy reconstructions, but only by using extremely high atmospheric CO2 concentrations or more modest CO2 levels complemented by a reduction in global cloud albedo. Understanding the mix of radiative forcing that gave rise to Eocene warmth has important implications for constraining Earth's climate sensitivity, but progress in this direction is hampered by the lack of direct proxy constraints on cloud properties. Here, we explore the potential for distinguishing among different radiative forcing scenarios via their impact on regional climate changes. We do this by comparing climate model simulations of two end-member scenarios: one in which the climate is warmed entirely by CO2 (which we refer to as the greenhouse gas (GHG) scenario) and another in which it is warmed entirely by reduced cloud albedo (which we refer to as the low CO2–thin clouds or LCTC scenario) . The two simulations have an almost identical global-mean surface temperature and equator-to-pole temperature difference, but the LCTC scenario has  ∼  11 % greater global-mean precipitation than the GHG scenario. The LCTC scenario also has cooler midlatitude continents and warmer oceans than the GHG scenario and a tropical climate which is significantly more El Niño-like. Extremely high warm-season temperatures in the subtropics are mitigated in the LCTC scenario, while cool-season temperatures are lower at all latitudes. These changes appear large enough to motivate further, more detailed study using other climate models and a more realistic set of modelling assumptions.

scholarly journals The relevance of aerosol optical depth to cumulus fraction changes: a five-year climatology at the ACRF SGP site

2007 ◽  
Vol 7 (4) ◽  
pp. 11797-11837 ◽  
Author(s):  
E. I. Kassianov ◽  
L. K. Berg ◽  
C. Flynn ◽  
S. McFarlane
Keyword(s):  
Aerosol Optical Depth ◽  
Optical Depth ◽  
Great Plains ◽  
Value Added ◽  
Cloud Fraction ◽  
Satellite Observations ◽  
Time Dependent ◽  
Size Dependent ◽  
Cloud Properties ◽  
Moderate Resolution Imaging Spectroradiometer

Abstract. The objective of this study is to investigate, by observational means, the magnitude and sign of the actively discussed relationship between cloud fraction N and aerosol optical depth τa. Collocated and coincident ground-based measurements and Terra/Aqua satellite observations at the Atmospheric Radiation Measurement (ARM) Climate Research Facility (ACRF) Southern Great Plains (SGP) site form the basis of this study. The N–τa relationship occurred in a specific 5-year dataset of fair-weather cumulus (FWC) clouds and mostly non-absorbing aerosols. To reduce possible contamination of the aerosols on the cloud properties estimation (and vice versa), we use independent datasets of τa and N obtained from the Multi-filter Rotating Shadowband Radiometer (MFRSR) measurements and from the ARM Active Remotely Sensed Clouds Locations (ARSCL) value-added product, respectively. Optical depth of the FWC clouds τcld and effective radius of cloud droplets re are obtained from the MODerate resolution Imaging Spectroradiometer (MODIS) data. We found that relationships between cloud properties (N,τcld, re) and aerosol optical depth are time-dependent (morning versus afternoon). Observed time-dependent changes of cloud properties, associated with aerosol loading, control the variability of surface radiative fluxes. In comparison with pristine clouds, the polluted clouds are more transparent in the afternoon due to smaller cloud fraction, smaller optical depth and larger droplets. As a result, the corresponding correlation between the surface radiative flux and τa is positive (warming effect of aerosol). Also we found that relationship between cloud fraction and aerosol optical depth is cloud size dependent. The cloud fraction of large clouds (larger than 1 km) is relatively insensitive to the aerosol amount. In contrast, cloud fraction of small clouds (smaller than 1 km) is strongly positively correlated with τa. This suggests that an ensemble of polluted clouds tends to be composed of smaller clouds than a similar one in a pristine environment. One should be aware of these time- and size-dependent features when qualitatively comparing N–τa relationships obtained from the satellite observations, surface measurements, and model simulations.

scholarly journals Evaluating Models' Response Of Tropical Low Clouds to SST Forcings Using CALIPSO Observations

2018 ◽  
Author(s):  
Gregory Cesana ◽  
Anthony D. Del Genio ◽  
Andrew S. Ackerman ◽  
Maxwell Kelley ◽  
Gregory Elsaesser ◽  
...  
Keyword(s):  
Surface Temperature ◽  
Vertical Structure ◽  
Climate Models ◽  
Climate Model ◽  
Cloud Fraction ◽  
Surface Warming ◽  
Cloud Radiative Effect ◽  
Low Cloud ◽  
Moist Processes ◽  
Low Cloud Cover

Abstract. Recent studies have shown that in response to a surface warming, the marine tropical low-cloud cover (LCC) as observed by passive sensor satellites substantially decreases, therefore generating a smaller negative value of the top-of-the-atmosphere cloud radiative effect (CRE). Here we study the LCC and CRE interannual changes in response to sea surface temperature (SST) forcings in the GISS Model E2 climate model, a developmental version of the GISS Model E3 climate model, and in 12 other climate models, as a function of their ability to represent the vertical structure of the cloud response to SST change against 10 years of CALIPSO observations. The more realistic models (those that satisfy the observational constraint) capture the observed interannual LCC change quite well (ΔLCC/ΔSST = −3.49 ± 1.01 % K−1 vs. ΔLCC/ΔSSTobs = −3.59 ± 0.28 % K−1) while the others largely underestimate it (ΔLCC/ΔSST = −1.32 ± 1.28 % K−1). Consequently, the more realistic models simulate more positive shortwave feedback (ΔCRE/ΔSST = 2.60 ± 1.13 W m−2 K−1) than the less realistic models (ΔCRE/ΔSST = 0.87 ± 2.63 W m−2 K−1), in better agreement with the observations (ΔCRE/ΔSSTobs = 3.05 ± 0.28 W m−2 K−1), although slightly underestimated. The ability of the models to represent moist processes within the planetary boundary layer and produce persistent stratocumulus decks appears crucial to replicating the observed relationship between clouds, radiation and surface temperature. This relationship is different depending on the type of low cloud in the observations. Over stratocumulus regions, cloud top height increases slightly with SST, accompanied by a large decrease of cloud fraction, whereas over trade cumulus regions, cloud fraction decreases everywhere, to a smaller extent.

Discrepancy in radiative feedbacks between models and observations tied to models inability to reproduce historical surface temperature patterns over the tropical Indo-Pacific.

2020 ◽  
Author(s):  
Cristian Proistosescu ◽  
Yue Dong ◽  
Malte Stuecker ◽  
Kyle Armour ◽  
Robb Wills ◽  
...  
Keyword(s):  
Surface Temperature ◽  
Climate Sensitivity ◽  
Climate Models ◽  
Atmospheric Model ◽  
Natural Variability ◽  
Forced Response ◽  
Large Ensemble ◽  
Radiative Feedback ◽  
Wide Range ◽  
Radiative Feedbacks

<p>How much Earth warms in response to radiative forcing is determined by the net radiative feedback, which quantifies how much more energy is radiated to space for a given increase in surface temperature.  Estimates from present day observations of temperature and earth's energetic imbalance yield a strongly negative radiative feedback, or, equivalently, a very low climate sensitivity, which lies outside the range of climate sensitivity in coupled climate models. This discrepancy in radiative feedbacks can be linked to discrepancies between models and observations in the pattern of historical sea-surface temperature (SST) anomalies driving tropical atmospheric circulation and radiative damping.  Indeed, we find that an atmospheric model (CAM5) forced with observed SSTs yields a net feedback that is consistent with observational estimates, but up to three times more negative than that from the same period (2000-2017) in historical simulations where the same atmospheric model is coupled to a dynamical ocean model (CESM1). </p><p>To understand the role natural variability can play in this discrepancy, we compare the radiative feedbacks generated by the observed pattern of SSTs to those within the CESM1 large ensemble over the same period. The large ensemble produces a wide range of feedbacks due to internal variability alone. Yet, global radiative feedbacks (cloud feedbacks in particular) generated by observed warming patterns are far outside the range of natural variability in the large ensemble. Using both a Green's function approach, as well as a simple metric based on the East-West tropical pacific gradient, we show that none of the control simulations of CMIP5 climate models can generate sufficiently large natural variability to explain the discrepancy between models and observations. We conclude that the discrepancy in SST patterns, and the resulting discrepancy in radiative feedbacks, is caused by an deficiency in models' ability to simulate either natural variabilty or the forced response over the recent historical period. We will also show preliminary analysis from CMIP6 simulations.</p>

scholarly journals Relationship of tropospheric stability to climate sensitivity and Earth’s observed radiation budget

2017 ◽  
Vol 114 (50) ◽  
pp. 13126-13131 ◽  
Author(s):  
Paulo Ceppi ◽  
Jonathan M. Gregory
Keyword(s):  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Climate Sensitivity ◽  
Climate Models ◽  
Sea Surface ◽  
Lapse Rate ◽  
Radiation Budget ◽  
Climate Feedback ◽  
Temperature Pattern ◽  
Climate Feedbacks

Climate feedbacks generally become smaller in magnitude over time under CO2 forcing in coupled climate models, leading to an increase in the effective climate sensitivity, the estimated global-mean surface warming in steady state for doubled CO2. Here, we show that the evolution of climate feedbacks in models is consistent with the effect of a change in tropospheric stability, as has recently been hypothesized, and the latter is itself driven by the evolution of the pattern of sea-surface temperature response. The change in climate feedback is mainly associated with a decrease in marine tropical low cloud (a more positive shortwave cloud feedback) and with a less negative lapse-rate feedback, as expected from a decrease in stability. Smaller changes in surface albedo and humidity feedbacks also contribute to the overall change in feedback, but are unexplained by stability. The spatial pattern of feedback changes closely matches the pattern of stability changes, with the largest increase in feedback occurring in the tropical East Pacific. Relationships qualitatively similar to those in the models among sea-surface temperature pattern, stability, and radiative budget are also found in observations on interannual time scales. Our results suggest that constraining the future evolution of sea-surface temperature patterns and tropospheric stability will be necessary for constraining climate sensitivity.

scholarly journals Arctic Climate Variability and Trends from Satellite Observations

2012 ◽  
Vol 2012 ◽  
pp. 1-22 ◽  
Author(s):  
Xuanji Wang ◽  
Jeffrey Key ◽  
Yinghui Liu ◽  
Charles Fowler ◽  
James Maslanik ◽  
...  
Keyword(s):  
Climate Change ◽  
Sea Ice ◽  
Surface Temperature ◽  
Cloud Fraction ◽  
Arctic Sea Ice ◽  
Satellite Observations ◽  
Arctic Climate ◽  
The Arctic ◽  
Climate Indices ◽  
Surface Warming

Arctic climate has been changing rapidly since the 1980s. This work shows distinctly different patterns of change in winter, spring, and summer for cloud fraction and surface temperature. Satellite observations over 1982–2004 have shown that the Arctic has warmed up and become cloudier in spring and summer, but cooled down and become less cloudy in winter. The annual mean surface temperature has increased at a rate of 0.34°C per decade. The decadal rates of cloud fraction trends are −3.4%, 2.3%, and 0.5% in winter, spring, and summer, respectively. Correspondingly, annually averaged surface albedo has decreased at a decadal rate of −3.2%. On the annual average, the trend of cloud forcing at the surface is −2.11 W/m2per decade, indicating a damping effect on the surface warming by clouds. The decreasing sea ice albedo and surface warming tend to modulate cloud radiative cooling effect in spring and summer. Arctic sea ice has also declined substantially with decadal rates of −8%, −5%, and −15% in sea ice extent, thickness, and volume, respectively. Significant correlations between surface temperature anomalies and climate indices, especially the Arctic Oscillation (AO) index, exist over some areas, implying linkages between global climate change and Arctic climate change.

scholarly journals Quantification of Monthly Mean Regional-Scale Albedo of Marine Stratiform Clouds in Satellite Observations and GCMs

2011 ◽  
Vol 50 (10) ◽  
pp. 2139-2148 ◽  
Author(s):  
Frida A.-M. Bender ◽  
Robert J. Charlson ◽  
Annica M. L. Ekman ◽  
Louise V. Leahy
Keyword(s):  
Climate Models ◽  
System Modeling ◽  
Regional Scale ◽  
Radiant Energy ◽  
Energy System ◽  
Cloud Fraction ◽  
Satellite Observations ◽  
Radiative Properties ◽  
Cloud Albedo ◽  
Stratiform Clouds

AbstractPlanetary albedo—the reflectivity for solar radiation—is of singular importance in determining the amount of solar energy taken in by the Earth–atmosphere system. Modeling albedo, and specifically cloud albedo, correctly is crucial for realistic climate simulations. A method is presented herein by which regional cloud albedo can be quantified from the relation between total albedo and cloud fraction, which in observations is found to be approximately linear on a monthly mean scale. This analysis is based primarily on the combination of cloud fraction data from the Moderate Resolution Imaging Spectroradiometer (MODIS) and albedo data from the Clouds and the Earth’s Radiant Energy System (CERES), but the results presented are also supported by the combination of cloud fraction and proxy albedo data from satelliteborne lidar [Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO)]. These data are measured and derived completely independently from the CERES–MODIS data. Applied to low-level marine stratiform clouds in three regions (off the coasts of South America, Africa, and North America), the analysis reveals regionally uniform monthly mean cloud albedos, indicating that the variation in cloud shortwave radiative properties is small on this scale. A coherent picture of low “effective” cloud albedo emerges, in the range from 0.35 to 0.42, on the basis of data from CERES and MODIS. In its simplicity, the method presented appears to be useful as a diagnostic tool and as a constraint on climate models. To demonstrate this, the same method is applied to cloud fraction and albedo output from several current-generation climate models [from the Coupled Model Intercomparison Project, phase 3 (CMIP3), archive]. Although the multimodel mean cloud albedo estimates agree to within 20% with the satellite-based estimates for the three focus regions, model-based estimates of cloud albedo are found to display much larger variability than do the observations, within individual models as well as between models.

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